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Abstract Number: 116

Is Socioeconomic Status at Diagnosis Associated with Long-Term Direct Medical Costs in Systemic Sclerosis?  a General Population-Based Cohort Study

Natalie McCormick1, Mohsen Sadatsafavi2, Wenjia Chen3, Carlo A. Marra4 and J. Antonio Avina-Zubieta5, 1Faculty of Pharmaceutical Sciences, University of British Columbia/Arthritis Research Centre of Canada, Vancouver, BC, Canada, 2Division of Respiratory Medicine, University of British Columbia, Vancouver, BC, Canada, 3Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada, 4Pharm Sciences, Univ of British Columbia, Vancouver, BC, Canada, 5Rheumatology, Arthritis Research Centre of Canada, Richmond, BC, Canada

Meeting: 2014 ACR/ARHP Annual Meeting

Keywords: administrative databases, Health care cost, population studies, socioeconomic status and systemic sclerosis

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Session Information

Title: Health Services Research

Session Type: Abstract Submissions (ACR)

Background/Purpose:

Low socioeconomic status (SES) is associated with negative health outcomes and higher healthcare costs in general populations, but the impact of SES on costs in systemic sclerosis (SSc) is unknown. To address this knowledge gap, we examined the relationship between SES at diagnosis, and direct medical costs for 5 years after diagnosis, in a general population-based context. We hypothesized that baseline SES would be associated with higher costs.

 

Methods:

Data Source: Our administrative data captured all provincially funded outpatient encounters and hospitalizations (1990-2010), and all dispensed medications (1996-2010) regardless of funding source, in the province of British Columbia.

Sample: We assembled a general population-based cohort of all incident cases of SSc who received care from 1996-2010, based on the following validated algorithm: a) two ICD-9-CM codes for SSc at least 2 months apart but within a 2 year period by a non-rheumatologist physician; or b) one ICD code by a rheumatologist or hospitalization. Statistics Canada neighborhood income quintile data for the year of SSc diagnosis was used to define SES.

Cost Calculation: Costs for outpatient services and prescriptions were summed directly from billing data.  Case-mix methodology was used for hospitalizations. 

 

Statistical Analysis: Early mortality is common in SSc and likely associated with high costs before death, but failure to account for this censoring will underestimate the long-term costs of SSc. To address this, follow-up was divided into 90-day periods with costs per-period weighted by the person-specific inverse probability of being alive in each period.  A generalized linear model was used to

1) Evaluate the relationship between SES and direct medical costs, after adjusting for sex, age and baseline Charlson’s comorbidity index; and

2) Predict the cumulative 5-year costs (adjusted for censoring) for cases in each SES group. 

Parametric bootstrapping was used to obtain 95% confidence intervals (CI). Costs are reported in 2010 Canadian dollars.

Results:

We identified 1,116 incident SSc cases (83% female, mean age 56.2 years) contributing 3,392 person-years. 5-year costs totaled $36,559,914 with 24% from outpatient, 48% from hospital and 28% from medications.

Age (p=0.0278), Charlson’s co-morbidity score (p < 0.0001) and being in the lowest (p=0.0364) or middle (p=0.0015) SES quintile (vs. the highest) were significantly associated with costs.  Predicted cumulative 5-year costs for the lowest-SES cases were 42% greater than the highest-SES ($55,035 vs. $38,664). Highest-SES cases had the lowest medication costs (see Table). Cases in the middle SES quintile at diagnosis had the highest outpatient, hospital and overall costs.

Conclusion:

The long-term healthcare costs of SSc cases are substantial (averaging $51,643 per-person over 5 years), and associated with SES, being 42% greater, on-average, for the lowest-SES than the highest.

Socioeconomic Quintile

at Diagnosis

N Cases

N

Female

(%)

Mean Age at Diagnosis (SD)

Median Baseline Charlson Comorbidity Score (IQR)

N Months of Follow-Up

N

90-Day Costing Periods

N

Ever-Hospitalized (%)

Unadjusted Overall Costs

Covariate-Adjusted Mean

Per-Person Predicted Costs

(95% CI)

Outpatient

Hospital

Medication

Overall

All

1,116

922

(83%)

56.2

(14.6)

0 (1)

40,707

13,569

595

(53%)

$51,643

–

–

–

–

1=Lowest

220

178

(81%)

55.0

(14.1)

1 (2)

7,899

2,633

134

(61%)

$55,680

$11,373

($11,005 – $11,741)

$14,899

($12,380 – $17,418)

$17,161

($16,340 – $17,982)

$55,035

($52,516 – $57,554)

2

212

176

(83%)

55.0

(15.0)

0 (1)

7,599

2,533

118

(56%)

$43,680

$10,607

($10,104 – $11,111)

$8,750

($7,167 – $10,332)

$13,377

($12,769 – $13,985)

$43,169

($41,369 – $44,968)

3=Middle

239

204

(85%)

56.6

(15.3)

0 (1)

8,688

2,896

116

(49%)

$59,872

$14,251

($13,536 – $14,965)

$15,801

($13,403 – $18,199)

$14,963

($14,477 – $15,449)

$65,054

($60,939 – $69,170)

4

230

189

(82%)

56.4

(14.4)

1 (1)

8,484

2,828

125

(54%)

$54,007

$10,670

($10,265 – $11,075)

$10,230

($8,405 – $12,056)

$17,794

($16,975 – $18,612)

$51,381

($49,054 – $53,708)

5=Highest

215

175

(81%)

58.0

(14.0)

0 (1)

8,037

2,679

102

(47%)

$43,870

$11,033

($10,632 – $11,434)

$9,124

($7,768 – $10,481)

$11,979

($11,557 – $12,402)

$38,664

($37,159 – $40,169)


Disclosure:

N. McCormick,
None;

M. Sadatsafavi,
None;

W. Chen,
None;

C. A. Marra,
None;

J. A. Avina-Zubieta,
None.

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